Knowledge and RAG
Search and assistants connected to your company's authorised documents and data, with references to check the answers.
The challenge
Knowledge exists, but it is spread across documents, portals and databases that people must search separately.
Our approach
We organise sources, define updates and permissions, and design retrieval of relevant passages to support answers. We evaluate accuracy and behaviour when the sources are insufficient.
What we can deliver
- Source curation and update pipeline
- Semantic or hybrid search for the context
- Answers with references and access control
- Evaluations using representative questions
What is RAG?
Retrieval-augmented generation combines information retrieval with language generation. The application retrieves relevant content before answering, rather than relying only on a model's general knowledge.
A source is not a guarantee of accuracy
A citation helps people check an answer, but does not eliminate errors. Source quality, document versions, permissions and testing remain essential.